An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer.
The traditional view of cancer as a genetic disease that can successfully be treated with drugs targeting mutant onco-proteins has motivated whole-genome sequencing efforts in many human cancer types. However, only a subset of mutations found within the genomic landscape of cancer is likely to provi...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2015-09-01
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| Series: | PLoS Computational Biology |
| Online Access: | http://europepmc.org/articles/PMC4575033?pdf=render |
| _version_ | 1818586603282497536 |
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| author | Jasmine Foo Lin L Liu Kevin Leder Markus Riester Yoh Iwasa Christoph Lengauer Franziska Michor |
| author_facet | Jasmine Foo Lin L Liu Kevin Leder Markus Riester Yoh Iwasa Christoph Lengauer Franziska Michor |
| author_sort | Jasmine Foo |
| collection | DOAJ |
| description | The traditional view of cancer as a genetic disease that can successfully be treated with drugs targeting mutant onco-proteins has motivated whole-genome sequencing efforts in many human cancer types. However, only a subset of mutations found within the genomic landscape of cancer is likely to provide a fitness advantage to the cell. Distinguishing such "driver" mutations from innocuous "passenger" events is critical for prioritizing the validation of candidate mutations in disease-relevant models. We design a novel statistical index, called the Hitchhiking Index, which reflects the probability that any observed candidate gene is a passenger alteration, given the frequency of alterations in a cross-sectional cancer sample set, and apply it to a mutational data set in colorectal cancer. Our methodology is based upon a population dynamics model of mutation accumulation and selection in colorectal tissue prior to cancer initiation as well as during tumorigenesis. This methodology can be used to aid in the prioritization of candidate mutations for functional validation and contributes to the process of drug discovery. |
| first_indexed | 2024-12-16T08:55:35Z |
| format | Article |
| id | doaj.art-68add37970fa4186a1468d1ad4956f80 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-16T08:55:35Z |
| publishDate | 2015-09-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-68add37970fa4186a1468d1ad4956f802022-12-21T22:37:18ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582015-09-01119e100435010.1371/journal.pcbi.1004350An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer.Jasmine FooLin L LiuKevin LederMarkus RiesterYoh IwasaChristoph LengauerFranziska MichorThe traditional view of cancer as a genetic disease that can successfully be treated with drugs targeting mutant onco-proteins has motivated whole-genome sequencing efforts in many human cancer types. However, only a subset of mutations found within the genomic landscape of cancer is likely to provide a fitness advantage to the cell. Distinguishing such "driver" mutations from innocuous "passenger" events is critical for prioritizing the validation of candidate mutations in disease-relevant models. We design a novel statistical index, called the Hitchhiking Index, which reflects the probability that any observed candidate gene is a passenger alteration, given the frequency of alterations in a cross-sectional cancer sample set, and apply it to a mutational data set in colorectal cancer. Our methodology is based upon a population dynamics model of mutation accumulation and selection in colorectal tissue prior to cancer initiation as well as during tumorigenesis. This methodology can be used to aid in the prioritization of candidate mutations for functional validation and contributes to the process of drug discovery.http://europepmc.org/articles/PMC4575033?pdf=render |
| spellingShingle | Jasmine Foo Lin L Liu Kevin Leder Markus Riester Yoh Iwasa Christoph Lengauer Franziska Michor An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer. PLoS Computational Biology |
| title | An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer. |
| title_full | An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer. |
| title_fullStr | An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer. |
| title_full_unstemmed | An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer. |
| title_short | An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer. |
| title_sort | evolutionary approach for identifying driver mutations in colorectal cancer |
| url | http://europepmc.org/articles/PMC4575033?pdf=render |
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